Thomas Risberg

Software Engineer focusing on Cloud

New Hampshire, USA

My current focus is on "projectriff", designed for running Functions in response to Events. I also work on "Spring Cloud Data Flow", "Spring for Apache Hadoop" and "Spring Data JDBC Extensions" projects.

The Spring team hereby announces that the Spring for Apache Hadoop project will reach End-Of-Life status twelve months from today on April 5th, 2019. We will publish occasional 2.5.x maintenance releases as needed up until that point and will then move the project to the attic. The current Spring for Apache Hadoop 2.5.0 release is built using Apache Hadoop version 2.7.3 and should be compatible with the latest releases of the most popular Hadoop distributions.

Helm is a package manager for Kubernetes, similar to apt, yum or homebrew. It is very easy to install and it greatly simplifies installation of an application and its dependencies into your Kubernetes cluster. The application package contents and configuration is defined in a chart. When you install it you can override any default configuration values. Helm will install any required services in addition to the ones defined in the chart. For Spring Cloud Data Flow, you have three required services: MySQL and Redis are used as the stores for Spring Cloud Data Flow state and RabbitMQ is used for the pipelines' messaging layer.

This is a maintenance release where we focused on improving the reference documentation. Other improvements include addition of an OSS licensed JDBC driver for Microsoft SQL Server. The latest local deployer version can now handle apps built using Spring Boot 2.0 milestone releases.

On behalf of the team, I am excited to announce the release of the third milestone of Spring Cloud Data Flow 1.2.

Note: A great way to start using this new release(s) is to follow the release matrix on the project page, which includes the download coordinates and the links to the reference guide.

Highlights of the 1.2 M3 release:

Companion Metadata Artifact

As part of the long awaited feature to improve access to app properties info for both shell and Dashboard, we are introducing a new optional artifact for both Stream and Task applications - we are calling it the “companion metadata artifact”. Through this functionality, the streaming and task applications and their properties are first-class citizens for both Docker and Maven based application artifacts.

Performance optimizations to “stream list” operation. Instead of making individual calls for each app associated with the stream, the newly introduced MultiStateAppDeployer SPI operation invokes a call per stream that queries all the application statuses in a single network call

The most significant change for this release can be found in the Spring Cloud Deployer for Kubernetes project. Thanks to community contributions from Donovan Muller and Rémon (Ray) Sinnema, we have added support for defining volumes and volume mounts for deployed apps. We support the volume types that have a model supported by the Fabric8 Kubernetes client’s kubernetes-model.

Note: A great way to start using this new release(s) is to follow the release matrix on the project page, which includes the download coordinates and the links to the reference guide.

The most significant changes for this release can be found in the Spring Cloud Deployer for Kubernetes project. Thanks to several community contributions, we have significantly improved the customization options available for launching Kubernetes apps. We now support resource requests in addition to resource limits and the imagePullPolicy can now be specified. You can also specify the startup command and the entryPoint type used for the Docker image as well as override exposed ports and specify environment variables when deploying apps. For detailed list of deployer improvements review the changes listed in the Spring Cloud Deployer for Kubernetes 1.1.0.M1 marker.